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Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Risk Insights: Yusuf Moolla
29 episodes
3 weeks ago
Spoken by a human version of this article. TL;DR (TL;DL?) Complexity must be actively managed rather than passively accepted.Data relevance directly impacts both accuracy and explainability.Technical “visibility” techniques can be useful.About this podcast A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI. Hosted by Yusuf Moolla. Produced by Risk Insights (riskinsights.com.au).
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Management
Business
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All content for Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing is the property of Risk Insights: Yusuf Moolla and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Spoken by a human version of this article. TL;DR (TL;DL?) Complexity must be actively managed rather than passively accepted.Data relevance directly impacts both accuracy and explainability.Technical “visibility” techniques can be useful.About this podcast A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI. Hosted by Yusuf Moolla. Produced by Risk Insights (riskinsights.com.au).
Show more...
Management
Business
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Article 23. Algorithmic System Integrity: Testing
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
5 minutes
10 months ago
Article 23. Algorithmic System Integrity: Testing
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Spoken by a human version of this article. TL;DR (TL;DL?) Complexity must be actively managed rather than passively accepted.Data relevance directly impacts both accuracy and explainability.Technical “visibility” techniques can be useful.About this podcast A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI. Hosted by Yusuf Moolla. Produced by Risk Insights (riskinsights.com.au).